COVID-19 and Lung Mast Cells: The Kallikrein–Kinin Activation Pathway

Mast cells (MCs) have relevant participation in inflammatory and vascular hyperpermeability events, responsible for the action of the kallikrein–kinin system (KKS), that affect patients inflicted by the severe form of COVID-19. Given a higher number of activated MCs present in COVID-19 patients and their association with vascular hyperpermeability events, we investigated the factors that lead to the activation and degranulation of these cells and their harmful effects on the alveolar septum environment provided by the action of its mediators. Therefore, the pyroptotic processes throughout caspase-1 (CASP-1) and alarmin interleukin-33 (IL-33) secretion were investigated, along with the immunoexpression of angiotensin-converting enzyme 2 (ACE2), bradykinin receptor B1 (B1R) and bradykinin receptor B2 (B2R) on post-mortem lung samples from 24 patients affected by COVID-19. The results were compared to 10 patients affected by H1N1pdm09 and 11 control patients. As a result of the inflammatory processes induced by SARS-CoV-2, the activation by immunoglobulin E (IgE) and degranulation of tryptase, as well as Toluidine Blue metachromatic (TB)-stained MCs of the interstitial and perivascular regions of the same groups were also counted. An increased immunoexpression of the tissue biomarkers CASP-1, IL-33, ACE2, B1R and B2R was observed in the alveolar septum of the COVID-19 patients, associated with a higher density of IgE⁺ MCs, tryptase⁺ MCs and TB-stained MCs, in addition to the presence of intra-alveolar edema. These findings suggest the direct correlation of MCs with vascular hyperpermeability, edema and diffuse alveolar damage (DAD) events that affect patients with a severe form of this disease. The role of KKS activation in events involving the exacerbated increase in vascular permeability and its direct link with the conditions that precede intra-alveolar edema, and the consequent DAD, is evidenced. Therapy with drugs that inhibit the activation/degranulation of MCs can prevent the worsening of the prognosis and provide a better outcome for the patient.     

The effect of cocoa fermentation and weak organic acids on growth and ochratoxin A production by Aspergillus species

The acidic characteristics of cocoa beans have influence on flavor development in chocolate. Cocoa cotyledons are not naturally acidic, the acidity comes from organic acids produced by the fermentative microorganisms which grow during the processing of cocoa. Different concentrations of these metabolites can be produced according to the fermentation practices adopted in the farms, which could affect the growth and ochratoxin A production by fungi. This work presents two independent experiments carried out to investigate the effect of some fermentation practices on ochratoxin A production by Aspergillus carbonarius in cocoa, and the effect of weak organic acids such as acetic, lactic and citric at different pH values on growth and ochratoxin A production by A. carbonarius and Aspergillus niger in culture media. A statistical difference (ρ<0.05) in the ochratoxin A level in the cured cocoa beans was observed in some fermentation practices adopted. The laboratorial studies demonstrate the influence of organic acids on fungal growth and ochratoxin A production, with differences according to the media pH and the organic acid present. Acetic acid was the most inhibitory acid against A. carbonarius and A. niger. From the point of view of food safety, considering the amount of ochratoxin A produced, fermentation practices should be conducted towards the enhancement of acetic acid, although lactic and citric acids also have an important role in lowering the pH to improve the toxicity of acetic acid.     

Accurate and reliable image classification by using conformal predictors in the TJ-II Thomson scattering

The charge-coupled device camera of the TJ-II Thomson scattering (TS) can capture five different classes of images. Typically, different data processing is performed depending on the kind of image that is acquired. The procedure can be automated to recognize the type of image. To this end, machine learning methods (MLM) are applied. However, usually, MLM classify without confidence estimates. An image classifier based on conformal predictors has been developed for the TJ-II TS. It provides a couple of indicators (confidence and credibility) for each classification that measures the accuracy and reliability of the prediction. Results achieve success rates of about 97%. The implemented classifier is valid for any kind of images.     

An investigation of latency prediction for NoC-based communication architectures using machine learning techniques

The Journal of Supercomputing - Due to the increasing number of cores in Systems on Chip (SoCs), bus architectures have suffered with limitations regarding performance. As applications demand...     

Runtime verification of autopilot systems using a fragment of MTL- $${int }$$

International Journal on Software Tools for Technology Transfer - Current real-time embedded systems development frameworks lack support for the verification of properties using explicit time where...     

Periodic Copula Autoregressive Model Designed to Multivariate Streamflow Time Series Modelling

Water Resources Management - It is a challenge to develop models that can represent the stochastic behaviour of rivers and basins. Currently used streamflow models were constructed under rigid...